Files

295 lines
12 KiB
Python
Raw Permalink Normal View History

#!/usr/bin/env python3
"""Enrich Twenty CRM opportunities and companies from local job-search data.
Encodes the deterministic layers of the /sync-twenty enrichment pipeline:
Opportunity salary (``amount``), in source priority order:
1. seen_jobs.json ``salary_max_stated`` (stated in the posting at rank time)
2. jobs.db postings salary_max (same company+title, stated on an ATS board)
3. jobs.db companies levels_swe_median (levels.fyi company median - labeled estimate)
Company fields (``domainName``, ``linkedinLink``, ``address``, ``annualRevenue``):
- jobs.db companies row matched on normalized name, homepage domain joined
through postings.company_domain. Stringified NaN / empty strings are absent.
Anything these layers cannot ground is emitted in the plan's ``unresolved``
section for the calling command to escalate to web research (scout subagents /
Perplexity) - this script never guesses.
Usage:
python3 tools/twenty_enrich.py # plan -> job_scraper/enrichment_plan.json
python3 tools/twenty_enrich.py --apply # plan + apply via REST (needs TWENTY_API_KEY)
python3 tools/twenty_enrich.py --snapshot f.json # offline: CRM state from a JSON snapshot
Snapshot shape (what /sync-twenty exports through MCP):
{"opportunities": [{id, url:{primaryLinkUrl}, amount, closeDate, ...}],
"companies": [{id, name, domainName, linkedinLink, address, ...}]}
The plan JSON is idempotent to apply: every entry names the target record id
and only fields that are currently empty.
"""
from __future__ import annotations
import argparse
import json
import re
import sqlite3
import sys
from pathlib import Path
REPO = Path(__file__).resolve().parent.parent
SEEN_JOBS = REPO / "job_scraper" / "seen_jobs.json"
JOBS_DB = REPO / "documents" / "postings" / "jobs.db"
PLAN_OUT = REPO / "job_scraper" / "enrichment_plan.json"
_SUFFIXES = re.compile(r"\b(inc|llc|ltd|corp|corporation|co|labs|lab|hq|the)\b")
def norm_company(s: str) -> str:
"""Normalized company key: lowercase, punctuation collapsed, suffixes stripped."""
s = re.sub(r"[^a-z0-9]+", " ", (s or "").lower()).strip()
s = _SUFFIXES.sub("", s).strip()
return re.sub(r"\s+", " ", s)
def norm_title(s: str) -> str:
return re.sub(r"[^a-z0-9]+", " ", (s or "").lower()).strip()
def clean_domain(raw: str | None) -> str | None:
"""Bare registrable domain or None. Rejects the stringified-NaN artifact."""
if not raw:
return None
d = str(raw).strip().lower()
for prefix in ("http://", "https://", "www."):
d = d.removeprefix(prefix)
d = d.rstrip("/")
if not d or d == "nan" or "." not in d:
return None
return d
def _has_link(v) -> bool:
return bool(v and v.get("primaryLinkUrl"))
def _has_addr(v) -> bool:
return bool(v and (v.get("addressCity") or v.get("addressCountry")))
def _has_amount(v) -> bool:
return bool(v and v.get("amountMicros"))
def load_local_sources(seen_path: Path = SEEN_JOBS, db_path: Path = JOBS_DB):
"""Ranked jobs plus the jobs.db lookup tables the plan builders consume."""
seen = json.loads(seen_path.read_text(encoding="utf-8"))["seen"]
ranked = [v for v in seen.values() if v.get("status") == "ranked"]
db_companies: dict[str, dict] = {}
domains: dict[str, str] = {}
postings_salary: dict[tuple[str, str], int] = {}
levels: dict[str, int] = {}
if db_path.exists():
con = sqlite3.connect(db_path)
con.row_factory = sqlite3.Row
for r in con.execute(
"SELECT company_id, company_name, linkedin_url, country, state, apollo_city,"
" organization_revenue, levels_swe_median_usd, levels_median_comp_usd FROM companies"
):
key = norm_company(r["company_name"])
db_companies.setdefault(key, dict(r))
lv = r["levels_swe_median_usd"] or r["levels_median_comp_usd"]
if lv and lv > 0:
levels.setdefault(key, int(lv))
for r in con.execute(
"SELECT company_id, company_domain, COUNT(*) n FROM postings"
" WHERE company_domain IS NOT NULL AND company_domain != ''"
" GROUP BY company_id, company_domain ORDER BY n"
):
domains[r["company_id"]] = r["company_domain"] # last row = most frequent
for r in con.execute(
"SELECT company_name, title, salary_max, salary_currency FROM postings"
" WHERE salary_max IS NOT NULL AND salary_max > 0"
):
if (r["salary_currency"] or "USD").upper() in ("USD", "$", ""):
key = (norm_company(r["company_name"]), norm_title(r["title"]))
postings_salary.setdefault(key, int(float(r["salary_max"])))
con.close()
return ranked, db_companies, domains, postings_salary, levels
def build_salary_plan(ranked, opportunities, postings_salary, levels):
"""(updates, unresolved): amount patches for opportunities missing one."""
by_url = {}
for o in opportunities:
u = (o.get("url") or {}).get("primaryLinkUrl")
if u:
by_url[u] = o
updates, unresolved = [], []
for v in ranked:
o = by_url.get(v.get("url"))
if not o or _has_amount(o.get("amount")):
continue
amount = source = None
if v.get("salary_max_stated"):
amount, source = int(v["salary_max_stated"]), "seen_jobs.salary_max_stated"
else:
key = (norm_company(v.get("company", "")), norm_title(v.get("title", "")))
if key in postings_salary:
amount, source = postings_salary[key], "jobs.db postings"
elif norm_company(v.get("company", "")) in levels:
amount = levels[norm_company(v.get("company", ""))]
source = "levels.fyi company SWE median (estimate)"
if amount:
updates.append({
"id": o["id"],
"source": source,
"patch": {"amount": {"amountMicros": amount * 1_000_000, "currencyCode": "USD"}},
})
else:
unresolved.append({"id": o["id"], "url": v["url"],
"company": v.get("company"), "title": v.get("title")})
return updates, unresolved
def build_company_plan(companies, db_companies, domains):
"""(updates, unresolved): fill ONLY empty company fields from jobs.db."""
updates, unresolved = [], []
for c in companies:
key = norm_company(c.get("name", ""))
m = db_companies.get(key) or {}
patch = {}
if not _has_link(c.get("domainName")):
dom = clean_domain(domains.get(m.get("company_id", "")))
if dom:
patch["domainName"] = {"primaryLinkUrl": f"https://{dom}",
"primaryLinkLabel": c["name"]}
if not _has_link(c.get("linkedinLink")):
li = (m.get("linkedin_url") or "").strip()
if li:
patch["linkedinLink"] = {"primaryLinkUrl": li.replace("http://", "https://"),
"primaryLinkLabel": c["name"]}
if not _has_addr(c.get("address")):
addr = {k: v for k, v in [("addressCity", m.get("apollo_city")),
("addressState", m.get("state")),
("addressCountry", m.get("country"))] if v}
if addr:
patch["address"] = addr
if patch:
updates.append({"id": c["id"], "name": c["name"], "patch": patch})
# Fields still empty after the local layer -> web-research escalation
missing = []
if not _has_link(c.get("domainName")) and "domainName" not in patch:
missing.append("domain")
if not _has_link(c.get("linkedinLink")) and "linkedinLink" not in patch:
missing.append("linkedin")
if not _has_addr(c.get("address")) and "address" not in patch:
missing.append("address")
if missing:
unresolved.append({"id": c["id"], "name": c["name"], "missing": missing})
return updates, unresolved
def build_name_cleanup_plan(opportunities):
"""Strip the ' — <Company>' suffix from opportunity names.
Runs LAST, and only for opportunities whose company relation is already
set: the suffix is the human-readable fallback while the record is
unlinked, and becomes redundant once ``companyId`` points at the Company.
An unlinked opportunity keeps its suffixed name so it stays identifiable.
"""
updates = []
for o in opportunities:
name = o.get("name") or ""
if o.get("companyId") and " — " in name:
role = name.split(" — ")[0].strip()
if role and role != name:
updates.append({"id": o["id"], "patch": {"name": role}})
return updates
def coverage(opportunities, companies) -> dict:
n, m = len(companies), len(opportunities)
return {
"companies": {
"total": n,
"domain": sum(1 for c in companies if _has_link(c.get("domainName"))),
"linkedin": sum(1 for c in companies if _has_link(c.get("linkedinLink"))),
"address": sum(1 for c in companies if _has_addr(c.get("address"))),
},
"opportunities": {
"total": m,
"salary": sum(1 for o in opportunities if _has_amount(o.get("amount"))),
"company_link": sum(1 for o in opportunities if o.get("companyId")),
"score": sum(1 for o in opportunities if o.get("score") is not None),
},
}
def main(argv=None) -> int:
ap = argparse.ArgumentParser(description=__doc__.splitlines()[0])
ap.add_argument("--snapshot", type=Path,
help="CRM state JSON (offline mode; else fetched via REST)")
ap.add_argument("--apply", action="store_true",
help="apply the plan via Twenty REST (needs TWENTY_API_KEY)")
ap.add_argument("--out", type=Path, default=PLAN_OUT, help="plan output path")
args = ap.parse_args(argv)
ranked, db_companies, domains, postings_salary, levels = load_local_sources()
client = None
if args.snapshot:
snap = json.loads(args.snapshot.read_text(encoding="utf-8"))
opportunities, companies = snap["opportunities"], snap["companies"]
else:
from twenty_client import TwentyClient # noqa: deferred import keeps offline mode key-free
client = TwentyClient()
opportunities = client.list_all("opportunities")
companies = client.list_all("companies")
sal_updates, sal_unresolved = build_salary_plan(ranked, opportunities, postings_salary, levels)
comp_updates, comp_unresolved = build_company_plan(companies, db_companies, domains)
name_updates = build_name_cleanup_plan(opportunities)
plan = {
"coverage_before": coverage(opportunities, companies),
"opportunity_updates": sal_updates,
"company_updates": comp_updates,
"name_cleanup": name_updates,
"unresolved": {
"opportunities_without_salary": sal_unresolved,
"companies_missing_fields": comp_unresolved,
},
}
if args.apply:
if client is None:
from twenty_client import TwentyClient
client = TwentyClient()
for u in sal_updates:
client.update_one("opportunities", u["id"], u["patch"])
for u in comp_updates:
client.update_one("companies", u["id"], u["patch"])
# Name cleanup LAST: it must observe the post-link state.
for u in name_updates:
client.update_one("opportunities", u["id"], u["patch"])
plan["applied"] = {"opportunities": len(sal_updates), "companies": len(comp_updates),
"names_cleaned": len(name_updates)}
args.out.parent.mkdir(parents=True, exist_ok=True)
args.out.write_text(json.dumps(plan, indent=2), encoding="utf-8")
cov = plan["coverage_before"]
print(f"plan -> {args.out}")
print(f"opportunity salary updates: {len(sal_updates)} "
f"(coverage {cov['opportunities']['salary']}/{cov['opportunities']['total']} before)")
print(f"company field updates: {len(comp_updates)} · name cleanups: {len(name_updates)}")
print(f"unresolved -> web research: {len(sal_unresolved)} postings, "
f"{len(comp_unresolved)} companies")
if args.apply:
print("applied via REST.")
return 0
if __name__ == "__main__":
sys.exit(main())